Identifying Individualized Functional Brain Networks: An Unsupervised Deep Temporal Attention Based Autoencoder Model

• Published in: Proceedings (International Symposium on Biomedical Imaging) pp. 1 - 5
• Main Authors: Wang, Kexin, Ren, Yudan, Liu, Zhengyang, Yin, Song, Ding, Zhenqing, Li, Xiao, He, Xiaowei
• Format: Conference Proceeding
• Language: English
• Published: IEEE 27.05.2024
• Subjects: Brain modeling; Correlation; Deep learning; FBN identification; Feature extraction; Fingerprint recognition; Individualized FBNs; Naturalistic fMRI; Neural activity; Self-attention mechanisms; Vectors

Identifying functional brain networks (FBNs) under naturalistic stimuli is crucial for understanding the brain function. While numerous studies have employed deep learning methods to model neural responses, most of them overlook self-attention mechanism of brain and the temporal dependencies in neur...